An Automated Vehicle Tracking System Using Haar-Cascade Classifiers and Optical Character Recognition Engine

A secure lifestyle and travel are in high demand among individuals in this period of rapidly developing technologies. The number of automobiles on the road has grown over the last ten years. Being statistical, in 2009 the number of vehicles on the road was 115 million in India. After a decade, in 2019,the number increased to 295.77 million. As the automotive industry continues to develop dramatically on a daily basis, tracking individual vehicles becomes a very difficult undertaking. With the assistance of the security cameras on the side of the road, we propose an automated vehicle tracking system. For object detection, machine learning techniques like Haar-cascade classifiers are used. The text extraction is done by an Optical Character Recognition Engine called Easy OCR. The proposed work is divided into three main phases. The car is identified from each frame of the video in the first stage, which involves turning the video footage into pictures. The following stage is identifying the licence plate from the identified autos. From the observed number plates in the last step, the number plate characters are recognised.

I. Introduction

Every country now has a serious issue with traffic management and the identification of vehicles that violate the law. Because of excessive speed and other factors, it might be challenging to identify the driver of a vehicle that has broken the law in some cases. Software development becomes necessary as a result. Because licence plates differ from nation to country in terms of numbering systems, colours, character languages, styles, and sizes, more study is still needed in this field, despite the development of several methodologies, strategies, and algorithms for licence plate detection and recognition.